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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Metrics Concepts | 15% | - Core Metrics Data Model
|
| Topic 2: Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Topic 3: Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Topic 4: Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
| Topic 5: Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Topic 6: Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Topic 7: Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Topic 8: Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
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NEW QUESTION # 41
What constitutes a single metrics time series (MTS)?
Answer: C
Explanation:
Explanation
The correct answer is B. A set of data points that all have the same metric name and list of dimensions.
A metric time series (MTS) is a collection of data points that have the same metric and the same set of dimensions. For example, the following sets of data points are in three separate MTS:
MTS1: Gauge metric cpu.utilization, dimension "hostname": "host1" MTS2: Gauge metric cpu.utilization, dimension "hostname": "host2" MTS3: Gauge metric memory.usage, dimension "hostname": "host1" A metric is a numerical measurement that varies over time, such as CPU utilization or memory usage. A dimension is a key-value pair that provides additional information about the metric, such as the hostname or the location. A data point is a combination of a metric, a dimension, a value, and a timestamp1
NEW QUESTION # 42
Which of the following statements are true about the datatable on a chart? (Choose all that apply.)
Answer: A,C
Explanation:
By default, all dimensions of the output signal are displayed in a chart's datatable, and users can select which of these dimensions to show or hide to customize the view.
NEW QUESTION # 43
A customer is sending data from a machine that is over-utilized. Because of a lack of system resources, datapoints from this machine are often delayed by up to 10 minutes. Which setting can be modified in a detector to prevent alerts from firing before the datapoints arrive?
Answer: C
Explanation:
The correct answer is A. Max Delay.
Max Delay is a parameter that specifies the maximum amount of time that the analytics engine can wait for data to arrive for a specific detector. For example, if Max Delay is set to 10 minutes, the detector will wait for only a maximum of 10 minutes even if some data points have not arrived. By default, Max Delay is set to Auto, allowing the analytics engine to determine the appropriate amount of time to wait for data points1 In this case, since the customer knows that the data from the over-utilized machine can be delayed by up to 10 minutes, they can modify the Max Delay setting for the detector to 10 minutes. This will prevent the detector from firing alerts before the data points arrive, and avoid false positives or missing data1 To learn more about how to use Max Delay in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/observability/alerts-detectors-notifications/detector-options.html#Max-Delay
NEW QUESTION # 44
A customer is experiencing issues getting metrics from a new receiver they have configured in the OpenTelemetry Collector. How would the customer go about troubleshooting further with the logging exporter?
Answer: D
Explanation:
Explanation
The correct answer is B. Adding logging into the metrics receiver pipeline.
The logging exporter is a component that allows the OpenTelemetry Collector to send traces, metrics, and logs directly to the console. It can be used to diagnose and troubleshoot issues with telemetry received and processed by the Collector, or to obtain samples for other purposes1 To activate the logging exporter, you need to add it to the pipeline that you want to diagnose. In this case, since you are experiencing issues with a new receiver for metrics, you need to add the logging exporter to the metrics receiver pipeline. This will create a new plot that shows the metrics received by the Collector and any errors or warnings that might occur1 The image that you have sent with your question shows how to add the logging exporter to the metrics receiver pipeline. You can see that the exporters section of the metrics pipeline includes logging as one of the options.
This means that the metrics received by any of the receivers listed in the receivers section will be sent to the logging exporter as well as to any other exporters listed2 To learn more about how to use the logging exporter in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/components/logging-exporter.html 2:
https://docs.splunk.com/Observability/gdi/opentelemetry/exposed-endpoints.html
NEW QUESTION # 45
A customer wants to share a collection of charts with their entire SRE organization. What feature of Splunk Observability Cloud makes this possible?
Answer: D
Explanation:
Explanation
According to the web search results, dashboard groups are a feature of Splunk Observability Cloud that allows you to organize and share dashboards with other users in your organization1. You can create dashboard groups based on different criteria, such as service, team, role, or topic. You can also set permissions for each dashboard group, such as who can view, edit, or manage the dashboards in the group. Dashboard groups make it possible to share a collection of charts with your entire SRE organization, or any other group of users that you want to collaborate with.
NEW QUESTION # 46
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